No abstract

We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

International migration affects all countries of the world. It is anticipated that in an increasingly interconnected world, migration will increase. People migrate for various reasons ranging from pursuing a better life to reuniting with families to escaping war and natural disaster. While progress has been made in understanding the drivers of migration, there is still much to be learned to monitor and predict migration flows. We do not know how many people leave their country to settle elsewhere, either temporarily or permanently, and we know little about these migrants. The impact of migration on the individual and on sending and receiving communities and countries is only partly understood. The economic effects can be very different from the impacts on society and culture. We advocate a comprehensive approach to the study of migration that involves (a) better measurement, (b) greater insight into factors and actors that either initiate migration flows or perpetuate and reinforce flows, (c) greater insight into the emergence of migration systems, i.e. systems linking people, families and communities in different countries, (d) greater insight into the consequences of migration for the individual, communities and society at large, and (e) much better performance in predicting migration flows and migrant characteristics. The lack of knowledge creates huge systemic risks and uncertainties and frustrates the formation of effective policies. In this contribution, we review what we know and what we should know. We conclude with priorities for data collection, research and training.